Conspicuity of colorectal polyps at CT colonography: visual assessment, CAD performance, and the important role of polyp height

Appearances of screen-detected versus symptomatic colorectal cancers at CT colonography

OBJECTIVES

The aim of this study was to compare the morphology, radiological stage, conspicuity, and computer-assisted detection (CAD) characteristics of colorectal cancers (CRC) detected by computed tomographic colonography (CTC) in screening and symptomatic populations.

METHODS

Two radiologists independently analyzed CTC images from 133 patients diagnosed with CRC in (a) two randomized trials of symptomatic patients (35 patients with 36 tumours) and (b) a screening program using fecal occult blood testing (FOBt; 98 patients with 100 tumours), measuring tumour length, volume, morphology, radiological stage, and subjective conspicuity. A commercial CAD package was applied to both datasets. We compared CTC characteristics between screening and symptomatic populations with multivariable regression.

RESULTS

Screen-detected CRC were significantly smaller (mean 3.0 vs 4.3 cm, p < 0.001), of lower volume (median 9.1 vs 23.2 cm3, p < 0.001) and more frequently polypoid (34/100, 34 % vs. 5/36, 13.9 %, p = 0.02) than symptomatic CRC. They were of earlier stage than symptomatic tumours (OR = 0.17, 95 %CI 0.07-0.41, p < 0.001), and were judged as significantly less conspicuous (mean conspicuity 54.1/100 vs. 72.8/100, p < 0.001). CAD detection was significantly lower for screen-detected (77.4 %; 95 %CI 67.9-84.7 %) than symptomatic CRC (96.9 %; 95 %CI 83.8-99.4 %, p = 0.02).

CONCLUSIONS

Screen-detected CRC are significantly smaller, more frequently polypoid, subjectively less conspicuous, and less likely to be identified by CAD than those in symptomatic patients.

KEY POINTS

• Screen-detected colorectal cancers (CRC) are significantly smaller than symptomatic CRC. • Screening cases are significantly less conspicuous to radiologists than symptomatic tumours. • Screen-detected CRC have different morphology compared to symptomatic tumours (more polypoid, fewer annular). • A commercial computer-aided detection (CAD) system was significantly less likely to note screen-detected CRC.

CAD-associated reader error in CT colonography

RATIONALE AND OBJECTIVES

Computed tomographic colonographic interpretation with computer-aided detection (CAD) may be superior to unaided viewing, although polyp characteristics may influence accuracy. Reader error due to polyp characteristics was evaluated in a multiple-case, multiple-reader trial of computed tomographic colonography with CAD.

MATERIALS AND METHODS

Two experts retrospectively reviewed 52 positive cases (74 polyps) and categorized them as hard, moderate, or easy to detect. Each case was evaluated without and with CAD. Features that may influence a reader's ability to detect a polyp or to accept or reject a CAD mark were tabulated. The association between polyp characteristics and detection rates in the trial was assessed. The difference in detection rates (CAD vs unassisted) was calculated, and regression analysis was performed.

RESULTS

Of 64 polyps found by CAD, experts categorized 20 as hard, 28 as moderate, and 16 as easy to detect. Reader characterization errors predominated (47.3%) over other errors. Factors associated with lower detection rates included small size, flat morphology, and resemblance to a thickened fold. CAD was superior for polyps resembling lipomas compared to those that did not resemble lipomas (average increase in detection rate with CAD, 12.8% vs 5.5%; P < .05).

CONCLUSIONS

Polyp characteristic may impair computed tomographic colonographic interpretation augmented by CAD. Readers can avoid errors of measurement by evaluating diminutive polyp candidates with sample measurements. Caution should be taken when evaluating focally thick folds and when using visual impression to dismiss a polyp candidate as a lipoma when it is submerged in densely tagged fluid.

Computer-aided detection of colorectal polyps in CT colonography with and without fecal tagging: a stand-alone evaluation

PURPOSE

To evaluate the stand-alone performance of a computer-aided detection (CAD) algorithm for colorectal polyps in a large heterogeneous CT colonography (CTC) database that included both tagged and untagged datasets.

METHODS

Written, informed consent was waived for this institutional review board-approved, HIPAA-compliant retrospective study. CTC datasets from 2063 patients were assigned to training (n = 374) and testing (n = 1689). The test set consisted of 836 untagged and 853 tagged examinations not used for CAD training. Examinations were performed at 15 sites in the United States, Asia, and Europe, using 4- to 64-multidetector-row computed tomography and various acquisition parameters. CAD sensitivities were calculated on a per-patient and per-polyp basis for polyps measuring ≥6 mm. The reference standard was colonoscopy in 1588 (94%) and consensus interpretation by expert radiologists in 101 (6%) patients. Statistical testing employed χ, logistic regression, and Mann-Whitney U tests.

RESULTS

In 383 of 1689 individuals, 564 polyps measuring ≥6 mm were identified by the reference standard (347 polyps: 6-9 mm and 217 polyps: ≥10 mm). Overall, CAD per-patient sensitivity was 89.6% (343/383), with 89.0% (187/210) for untagged and 90.2% (156/173) for tagged datasets (P = 0.72). Overall, per-polyp sensitivity was 86.9% (490/564), with 84.4% (270/320) for untagged and 90.2% (220/244) for tagged examinations (P = 068). The mean false-positive rate per patient was 5.14 (median, 4) in untagged and 4.67 (median, 4) in tagged patient datasets (P = 0.353).

CONCLUSION

Stand-alone CAD can be applied to both tagged and untagged CTC studies without significant performance differences. Detection rates are comparable to human readers at a relatively low false-positive rate, making CAD a useful tool in clinical practice.

Sources of false positives in computer-assisted CT colonography

The application of computer-aided detection (CAD) is expected to improve reader sensitivity and to reduce inter-observer variance in computed tomographic (CT) colonography. However, current CAD systems display a large number of false-positive (FP) detections. The reviewing of a large number of FP CAD detections increases interpretation time, and it may also reduce the specificity and/or sensitivity of a computer-assisted reader. Therefore, it is important to be aware of the patterns and pitfalls of FP CAD detections. This pictorial essay reviews common sources of FP CAD detections that have been observed in the literature and in our experiments in computer-assisted CT colonography. Also the recommended computer-assisted reading technique is described.

ACRIN CT colonography trial: does reader's preference for primary two-dimensional versus primary three-dimensional interpretation affect performance?

PURPOSE

To determine whether the reader's preference for a primary two-dimensional (2D) or three-dimensional (3D) computed tomographic (CT) colonographic interpretation method affects performance when using each technique.

MATERIALS AND METHODS

In this institutional review board-approved, HIPAA-compliant study, images from 2531 CT colonographic examinations were interpreted by 15 trained radiologists by using colonoscopy as a reference standard. Through a survey at study start, study end, and 6-month intervals, readers were asked whether their interpretive preference in clinical practice was to perform a primary 2D, primary 3D, or both 2D and 3D interpretation. Readers were randomly assigned a primary interpretation method (2D or 3D) for each CT colonographic examination. Sensitivity and specificity of each method (primary 2D or 3D), for detecting polyps of 10 mm or larger and 6 mm or larger, based on interpretive preference were estimated by using resampling methods.

RESULTS

Little change was observed in readers' preferences when comparing them at study start and study end, respectively, as follows: primary 2D (eight and seven readers), primary 3D (one and two readers), and both 2D and 3D (six and six readers). Sensitivity and specificity, respectively, for identifying examinations with polyps of 10 mm or larger for readers with a primary 2D preference (n = 1128 examinations) were 0.84 and 0.86, which was not significantly different from 0.84 and 0.83 for readers who preferred 2D and 3D (n = 1025 examinations) or from 0.76 and 0.82 for readers with a primary 3D preference (n = 378 examinations). When performance by using the assigned 2D or 3D method was evaluated on the basis of 2D or 3D preference, there was no difference among those readers by using their preferred versus not preferred method of interpretation. Similarly, no significant difference among readers or preferences was seen when performance was evaluated for detection of polyps of 6 mm or larger.

CONCLUSION

The reader's preference for interpretive method had no effect on CT colonographic performance.

Polyp size measurement at CT colonography: what do we know and what do we need to know?

Polyp size is a critical biomarker for clinical management. Larger polyps have a greater likelihood of being or of becoming an adenocarcinoma. To balance the referral rate for polypectomy against the risk of leaving potential cancers in situ, sizes of 6 and 10 mm are increasingly being discussed as critical thresholds for clinical decision making (immediate polypectomy versus polyp surveillance) and have been incorporated into the consensus CT Colonography Reporting and Data System (C-RADS). Polyp size measurement at optical colonoscopy, pathologic examination, and computed tomographic (CT) colonography has been studied extensively but the reported precision, accuracy, and relative sizes have been highly variable. Sizes measured at CT colonography tend to lie between those measured at optical colonoscopy and pathologic evaluation. The size measurements are subject to a variety of sources of error associated with image acquisition, display, and interpretation, such as partial volume averaging, two- versus three-dimensional displays, and observer variability. This review summarizes current best practices for polyp size measurement, describes the role of automated size measurement software, discusses how to manage the measurement uncertainties, and identifies areas requiring further research.

Improving the accuracy of CTC interpretation: computer-aided detection

Computer-aided polyp detection aims to improve the accuracy of the colonography interpretation. The computer searches the colonic wall to look for polyplike protrusions and presents a list of suspicious areas to a physician for further analysis. Computer-aided polyp detection has developed rapidly in the past decade in the laboratory setting and has sensitivities comparable with those of experts. Computer-aided polyp detection tends to help inexperienced readers more than experienced ones and may also lead to small reductions in specificity. In its currently proposed use as an adjunct to standard image interpretation, computer-aided polyp detection serves as a spellchecker rather than an efficiency enhancer.

Comparison of 2D and 3D views for evaluation of flat lesions in CT colonography

RATIONALE AND OBJECTIVES

Flat lesions in the colon may result in false-negative computed tomography colonography interpretations. It is unknown whether flat lesions are better measured on two-dimensional (2D) or three-dimensional (3D) images and which settings are optimal for enhanced reproducibility and decreased variability. We evaluated these factors to determine whether 2D or 3D is best for flat lesion measurements.

METHODS AND MATERIALS

Eighty-eight lesions in 66 patients from a previously published clinical trial were analyzed. Lesions were viewed with four methods including 2D at three window/level settings and 3D endoluminal view. Lesions in either supine or prone were counted as one dataset. Long axis and height were measured. Criteria of "height" (<or=3 mm high) or "ratio" (height <or=half the long axis) were applied. A subset of lesions was subject to inter- and intra-observer variability analysis.

RESULTS

With the "height" criterion, more datasets were classified as flat in 2D flat (n = 76), 2D soft tissue (n = 82), and 3D (n = 73) views than in the 2D lung (n = 49) view. If long axis is used as the key metric, endoluminal 3D (12.1%) views significantly showed the least inter-observer variability compared to lung (18.9%) or soft tissue (20.2%) views. Intra-observer variability was low overall for all methods.

CONCLUSION

When characterizing lesions as flat, a consistent viewing method should be used. To minimize inter-observer variability (such as when following a patient over time), it is best to use the ratio criterion for flat lesion definition incorporating the single longest dimension on 3D views as the key metric.

Automated measurement of colorectal polyp height at CT colonography: hyperplastic polyps are flatter than adenomatous polyps

OBJECTIVE

Hyperplastic polyps are more difficult to detect than adenomatous polyps at CT colonography (CTC), and it has been theorized that this difference in detectability is because hyperplastic polyps are flatter. Using automated software that computes polyp height, we determined whether hyperplastic colonic polyps on CTC are indeed flatter than adenomatous polyps of comparable width.

MATERIALS AND METHODS

At three medical centers, 1,186 patients underwent oral contrast-enhanced CTC and same-day optical colonoscopy (OC) with segment unblinding for colorectal cancer screening. One hundred eighty-five of the patients had at least one hyperplastic or adenomatous polyp 6-10 mm visible at both OC and CTC, where size was determined by a calibrated guidewire at OC. To assess flatness, the heights of the polyps at CTC were measured using a validated automated software program. The heights and height-to-width ratios of the hyperplastic polyps were compared with those of the adenomatous polyps using a Student's t test (two-tailed, unpaired, unequal variance).

RESULTS

There were 176 adenomatous and 83 hyperplastic polyps visible at segment-unblinded OC. The fraction of these polyps that were measurable at CTC using the automated software was not significantly different for adenomatous versus hyperplastic polyps (158/176 [89.8%] vs 73/87 [83.9%], respectively; p = 0.2). The average height-to-width ratios using automated width measurements were 15% less for hyperplastic polyps: 0.39 +/- 0.20 (n = 158) and 0.33 +/- 0.19 (n = 73) for adenomatous and hyperplastic polyps, respectively (p = 0.03). When polyps of comparable OC size or CTC width were considered, the heights of hyperplastic polyps were up to 27% less than those of adenomatous polyps.

CONCLUSION

For 6-10 mm polyps of a given size as determined by OC or a given width at CTC, hyperplastic polyps tend to be flatter (i.e., have lower height) compared with adenomatous polyps.

Polyp characteristics correctly annotated by computer-aided detection software but ignored by reporting radiologists during CT colonography

PURPOSE

To retrospectively describe the characteristics of polyps incorrectly dismissed by radiologists despite appropriate computer-aided detection (CAD) prompting during computed tomographic (CT) colonography.

MATERIALS AND METHODS

Ethics committee approval and patient informed consent were obtained from institutions that provided the data sets used in this HIPAA-compliant study. A total of 111 polyps that had a diameter of at least 6 mm and were detected with CAD were collated from three previous studies in which researchers investigated radiologist performance with and without CAD (total, 25 readers). Two new observers graded each polyp with predefined criteria, including polyp size, morphology, and location; data set quality; ease of visualization; tagging use and polyp coating; colonic curvature; CAD mark obscuration; and number of false-positive findings. The 86 polyps that were missed before CAD (those that were unreported by one or more original readers) were divided into those that remained unreported after CAD (no CAD gain, n = 36) and those that were reported correctly by at least one additional reader (CAD gain, n = 50). Logistic-regression analysis and the Fisher exact and Mann-Whitney tests were used to compare the results of both groups with each other and with a control group of 25 polyps, all of which were detected by readers without CAD.

RESULTS

Before CAD, polyps 10 mm in diameter or larger, those that were rated easy to visualize, and those that were uncoated by tagged fluid were less likely to be missed (72%, 76%, and 80% of control polyps vs 43%, 43%, and 59% of missed polyps, respectively; P < .001, P < .01, and P < .03, respectively). After CAD, the odds of CAD gain decreased with increasing polyp size (odds ratio, 0.92; 95% confidence interval: 0.85, 1.00; P = .04) and irregular morphology (odds ratio, 0.28; 95% confidence interval: 0.08, 0.92; P = .04).

CONCLUSION

Larger irregular polyps are a common source of incorrect radiologist dismissal, despite correct CAD prompting.

Flat lesions in CT colonography

Flat lesions have been a source of controversy because of concerns that CT colonography (CTC) is insensitive in detecting these lesions, yet they may harbor a high incidence of advanced neoplasia. The wide variation in the reported incidence of flat lesions may in part be due to the lack of a uniform definition of "flat", and in fact in many prior reports the inclusion criteria for flat are not even clearly specified. Emphasis on the more recent CTC literature suggests that when limited the target lesion to neoplasia (adenomas or adenocarcinoma), the incidence of flat lesions is low and most can be detected by CTC. Using fecal tagging and careful attention to the proper methods of searching for flat lesions with both 3D and 2D techniques can maximize the detection of flat lesions at CTC. Computer-aided detection may be helpful.

EMPLOYING TOPOGRAPHICAL HEIGHT MAP IN COLONIC POLYP MEASUREMENT AND FALSE POSITIVE REDUCTION

CT Colonography (CTC) is an emerging minimally invasive technique for screening and diagnosing colon cancers. Computer Aided Detection (CAD) techniques can increase sensitivity and reduce false positives. Inspired by the way radiologists detect polyps via 3D virtual fly-through in CTC, we borrowed the idea from geographic information systems to employ topographical height map in colonic polyp measurement and false positive reduction. After a curvature based filtering and a 3D CT feature classifier, a height map is computed for each detection using a ray-casting algorithm. We design a concentric index to characterize the concentric pattern in polyp height map based on the fact that polyps are protrusions from the colon wall and round in shape. The height map is optimized through a multi-scale spiral spherical search to maximize the concentric index. We derive several topographic features from the map and compute texture features based on wavelet decomposition. We then send the features to a committee of support vector machines for classification. We have trained our method on 394 patients (71 polyps) and tested it on 792 patients (226 polyps). Results showed that we can achieve 95% sensitivity at 2.4 false positives per patient and the height map features can reduce false positives by more than 50%. We compute the polyp height and width measurements and correlate them with manual measurements. The Pearson correlations are 0.74 (p=0.11) and 0.75 (p=0.17) for height and width, respectively.